Activity recognition gained relevance in recent years because of its numerous applications. Despite relevant improvements, current classifiers are still inaccurate in several usage conditions or require time-consuming training. In this paper we show how localisation data and common sense knowledge could be used to improve activity recognition. More specifically, given the GPS position of the user, we both gather (i) a list of neighbouring commercial activities using a reverse geo-coding service and (ii) classify the satellite image of the area with state-of-the-art techniques. The approach maps classification labels produced by the three classifiers (i.e., activity, reverse geocoding localisation, satellite imagery localisation) to concepts within the ConceptNet network for the sake of improving activity recognition accuracy.

Improving Activity Recognition via Satellite Imagery and Commonsense Knowledge / Bicocchi, Nicola; Fontana, Damiano; Zambonelli, Franco. - ELETTRONICO. - (2014), pp. 183-187. ((Intervento presentato al convegno 2014 25th International Workshop on Database and Expert Systems Applications (DEXA) tenutosi a Munich (D) nel Settembre 2014 [10.1109/DEXA.2014.48].

Improving Activity Recognition via Satellite Imagery and Commonsense Knowledge

BICOCCHI, Nicola;FONTANA, Damiano;ZAMBONELLI, Franco
2014

Abstract

Activity recognition gained relevance in recent years because of its numerous applications. Despite relevant improvements, current classifiers are still inaccurate in several usage conditions or require time-consuming training. In this paper we show how localisation data and common sense knowledge could be used to improve activity recognition. More specifically, given the GPS position of the user, we both gather (i) a list of neighbouring commercial activities using a reverse geo-coding service and (ii) classify the satellite image of the area with state-of-the-art techniques. The approach maps classification labels produced by the three classifiers (i.e., activity, reverse geocoding localisation, satellite imagery localisation) to concepts within the ConceptNet network for the sake of improving activity recognition accuracy.
2014 25th International Workshop on Database and Expert Systems Applications (DEXA)
Munich (D)
Settembre 2014
183
187
Bicocchi, Nicola; Fontana, Damiano; Zambonelli, Franco
Improving Activity Recognition via Satellite Imagery and Commonsense Knowledge / Bicocchi, Nicola; Fontana, Damiano; Zambonelli, Franco. - ELETTRONICO. - (2014), pp. 183-187. ((Intervento presentato al convegno 2014 25th International Workshop on Database and Expert Systems Applications (DEXA) tenutosi a Munich (D) nel Settembre 2014 [10.1109/DEXA.2014.48].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1060813
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